library(ggplot2)
library(gganimate)
## Warning: package 'gganimate' was built under R version 4.3.1
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.2     ✔ readr     2.1.4
## ✔ forcats   1.0.0     ✔ stringr   1.5.0
## ✔ lubridate 1.9.2     ✔ tibble    3.2.1
## ✔ purrr     1.0.1     ✔ tidyr     1.3.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(here)
## here() starts at D:/RK/UNSW/Data Visualisation/DATA5002/Project
library(gifski)
## Warning: package 'gifski' was built under R version 4.3.1
library(forcats)
library(animation)
## Warning: package 'animation' was built under R version 4.3.1
library(plotly)
## Warning: package 'plotly' was built under R version 4.3.1
## 
## Attaching package: 'plotly'
## 
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## 
## The following object is masked from 'package:stats':
## 
##     filter
## 
## The following object is masked from 'package:graphics':
## 
##     layout
library(highcharter)
## Warning: package 'highcharter' was built under R version 4.3.1
## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo
library(dplyr)
df <- read.csv(here("Data", "import_export_years.csv"))

head(df)
##   year import_export crude_oil  lpg  ms naphtha atf  sko   hsd ldo
## 1 1998        import     39808 1722 251    2407   0 7065 10231   0
## 2 1999        import     57805 1587   0    1917   0 6312  5006   0
## 3 2000        import     74097  853   0    3165   0 1918     0   0
## 4 2001        import     78706  659   0    3308   0  391    31   0
## 5 2002        import     81989 1073   0    2784   0  698   106   0
## 6 2003        import     90434 1708   0    2371   0  804   100   0
##   lobs_lube_oil fuel_oil bitumen others total
## 1           396     1696       0      3 63579
## 2           407     1377       0      1 74412
## 3           255     1728       0   1348 83364
## 4           326     1977       9    308 85715
## 5           340     2220       0      7 89217
## 6           612     1728       6    672 98435
# Split the data into import and export
import_data <- subset(df, import_export == 'import')
export_data <- subset(df, import_export == 'export')

# Calculate total import excluding crude oil
import_data_no_crude <- import_data
import_data_no_crude$total <- import_data_no_crude$total - import_data_no_crude$crude_oil
import_data_no_crude <- subset(import_data_no_crude, select = -crude_oil)
plt <- ggplot() +
  geom_line(data = import_data, aes(x = year, y = total, color = 'Import (Including Crude Oil)', linetype = 'Import (Including Crude Oil)')) +
  geom_point(data = import_data, aes(x = year, y = total)) +
  geom_line(data = import_data_no_crude, aes(x = year, y = total, color = 'Import (Excluding Crude Oil)', linetype = 'Import (Excluding Crude Oil)')) +
  geom_point(data = import_data_no_crude, aes(x = year, y = total)) +
  geom_line(data = export_data, aes(x = year, y = total, color = 'Export', linetype = 'Export')) +
  geom_point(data = export_data, aes(x = year, y = total)) +
  scale_color_manual(values = c('Import (Including Crude Oil)' = 'blue', 'Import (Excluding Crude Oil)' = 'blue', 'Export' = 'red'),
                     name = "Type",
                     breaks = c('Import (Including Crude Oil)', 'Import (Excluding Crude Oil)', 'Export'),
                     labels = c('Import (Including Crude Oil)', 'Import (Excluding Crude Oil)', 'Export')) +
  scale_linetype_manual(values = c('Import (Including Crude Oil)' = "solid", 'Import (Excluding Crude Oil)' = "dashed", 'Export' = "solid"),
                        name = "Type",
                        breaks = c('Import (Including Crude Oil)', 'Import (Excluding Crude Oil)', 'Export'),
                        labels = c('Import (Including Crude Oil)', 'Import (Excluding Crude Oil)', 'Export')) +
  scale_x_continuous(breaks = seq(min(import_data$year), max(import_data$year), by = 1)) +
  scale_y_continuous(n.breaks = 20) +
  labs(title = "Comparison of Imports (with and without Crude Oil) and Exports Over the Years",
       x = "Year",
       y = "Total Quantity") +
  theme_bw() +
  theme(legend.title = element_blank(),
        legend.position = c(0.9, 0.5),
        legend.justification = c(0.5, 0.5),
        legend.background = element_rect(fill="white",
                                  size=0.5, linetype="solid", 
                                  colour ="black"))
## Warning: The `size` argument of `element_rect()` is deprecated as of ggplot2 3.4.0.
## ℹ Please use the `linewidth` argument instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
plot(plt)

fig <- plot_ly() %>%
      add_trace(data = import_data, x = ~year, y = ~total, name = 'Import (Including Crude Oil)', type = 'scatter', mode = 'lines+markers', line = list(color = 'blue')) %>%
      add_trace(data = import_data_no_crude, x = ~year, y = ~total, name = 'Import (Excluding Crude Oil)', type = 'scatter', mode = 'lines+markers', line = list(color = 'blue', dash = 'dash')) %>%
      add_trace(data = export_data, x = ~year, y = ~total, name = 'Export', type = 'scatter', mode = 'lines+markers', line = list(color = 'red')) %>%
      layout(title = "Comparison of Imports (with and without Crude Oil) and Exports Over the Years",
             xaxis = list(title = "Year"),
             yaxis = list(title = "Total Quantity in '000 Metric Tons"))

fig
data_subset <- import_data

data_subset <- data_subset %>%
      filter(year == 1999) %>%
      select(-year, -import_export, -total) %>%
      gather(key = "Product", value = "Quantity")

data_subset
##          Product Quantity
## 1      crude_oil    57805
## 2            lpg     1587
## 3             ms        0
## 4        naphtha     1917
## 5            atf        0
## 6            sko     6312
## 7            hsd     5006
## 8            ldo        0
## 9  lobs_lube_oil      407
## 10      fuel_oil     1377
## 11       bitumen        0
## 12        others        1
plot_ly(data_subset, labels = ~Product, values = ~Quantity, type = 'pie') %>%
      layout(title = paste("Product Composition in", 1999))
sun <- read.csv(here("Data","import_export_months.csv"))
sun
##     year    months import_export crude_oil  lpg   ms naphtha atf sko  hsd ldo
## 1   2011   January        import     15737  419   20     153   0 129  508   0
## 2   2011  February        import     13784  469    0     133   0 141   40   0
## 3   2011     March        import     13935  482  215     162   0 111  192   0
## 4   2011     April        import     13750  495  135     227   0 110    0   0
## 5   2011       May        import     14264  428  108     122   0  73   16   0
## 6   2011      June        import     12990  504   36     202   0   0    1   0
## 7   2011      July        import     12463  453  140     182   0   0    5   0
## 8   2011    August        import     14850  447    0     274   0   0    2   0
## 9   2011 September        import     13933  475    0     240   0   0   22   0
## 10  2011   October        import     17017  512    0     111   0   0  207   0
## 11  2011  November        import     13719  514    0     108   0   0   62   0
## 12  2011  December        import     15289  592    0     175   0   0    4   0
## 13  2012   January        import     14809  655    0     138   0   0  133   0
## 14  2012  February        import     15627  628    0     173   0   0  109   0
## 15  2012     March        import     14817  459    0     179   0   0   61   0
## 16  2012     April        import     14594  526   57     187   0   0  132   0
## 17  2012       May        import     15045  528   90     190   0   0   63   0
## 18  2012      June        import     15236  592    0     188   0   0    2   0
## 19  2012      July        import     16503  508    0      85   0   0    1   0
## 20  2012    August        import     15495  509    0     214   0   0    2   0
## 21  2012 September        import     16021  533    0     112   0   0    8   0
## 22  2012   October        import     18345  448    0      95   0   0    8   0
## 23  2012  November        import     13366  383    0     120   0   0    5   0
## 24  2012  December        import     14936  531    0      81   0   0    5   0
## 25  2013   January        import     16408  520    0      66   0   0    6   0
## 26  2013  February        import     17181  601   15      66   0   0   17   0
## 27  2013     March        import     14310  345  115     125   0   0    0   0
## 28  2013     April        import     16353  400   76      95   0   0    1   0
## 29  2013       May        import     17573  553    0     100   0   0    3   0
## 30  2013      June        import     15082  573    0     156   0   0    1   0
## 31  2013      July        import     15361  643   29      73   0   0    3   0
## 32  2013    August        import     14614  352    0     108   0   0   29   0
## 33  2013 September        import     15822  666    0      93   0   0    4   0
## 34  2013   October        import     15503  713    0      66   0   0    2   0
## 35  2013  November        import     16515  651    0      56   0   0    7   0
## 36  2013  December        import     14516  551    0      17   0   0    5   0
## 37  2014   January        import     16902  657    0      46  10   0    0   0
## 38  2014  February        import     14905  633    0      66   5  30    5   0
## 39  2014     March        import     16211  564   61      69   0   0    2   0
## 40  2014     April        import     14222  711  143      72   5   0   51   0
## 41  2014       May        import     15990  624   50      99  14   0    1   0
## 42  2014      June        import     15989  758   20      62  21   0    6   0
## 43  2014      July        import     16193  721   38       0  14   0   10   0
## 44  2014    August        import     15005  651   16      23   5   0    8   0
## 45  2014 September        import     16820  816    0      47  14   0   10   0
## 46  2014   October        import     17715  711    0      86  19   0    3   0
## 47  2014  November        import     12993  623    0     137  11   0   10   0
## 48  2014  December        import     16489  843   44     327  20   0   18   0
## 49  2015   January        import     15535  685  120     152  19  35    1   0
## 50  2015  February        import     17454  809  154     364   6   0    0   0
## 51  2015     March        import     15619  653  170     347  55   6   10   0
## 52  2015     April        import     17732  696  133     354  25   0    2   0
## 53  2015       May        import     17235  996   38     296  24   0    1   0
## 54  2015      June        import     15787  663   51     165  20   0    1   0
## 55  2015      July        import     15568  710  143     242  20   0    7   0
## 56  2015    August        import     16636  724   33     122  27   0   10   0
## 57  2015 September        import     17726  785   98     205  26   0   10   0
## 58  2015   October        import     18129  803   53     230   6   0    2   0
## 59  2015  November        import     16882  684    0     205  20   0   72   0
## 60  2015  December        import     18546  750   20     248  36   0   62   0
## 61  2016   January        import     17960  809   74     326  23   0  503   0
## 62  2016  February        import     17527  857  157     219  28   0  222   0
## 63  2016     March        import     17630  796   38     238  33   0    3   0
## 64  2016     April        import     17214  811    0     269  27   0    1   0
## 65  2016       May        import     18811  746   90     249  25   0    0   0
## 66  2016      June        import     17762  798   84     238  43   0    0   0
## 67  2016      July        import     18153 1005    0     215   7   0    5   0
## 68  2016    August        import     18756 1021   33     252  34   0    3   0
## 69  2016 September        import     18006 1119    0     237  50   0  101   0
## 70  2016   October        import     17446  901    0      91  29   0  163   0
## 71  2016  November        import     16455 1000    0     209  32   0    5   0
## 72  2016  December        import     18212 1235    0     235   7   0    0   0
## 73  2017   January        import     18127  906    0      74  29   0   15   0
## 74  2017  February        import     17903  752    0     103  23   0  444   0
## 75  2017     March        import     17666  618   36      68  25   0  459   0
## 76  2017     April        import     17320  934  137     166  22   0  313   0
## 77  2017       May        import     18113 1105    0     168  24   0   12   0
## 78  2017      June        import     17644  872    0     185  25   0    1   0
## 79  2017      July        import     19029 1201    0     234  26   0    3   0
## 80  2017    August        import     19191 1233    0     117  34   0   18   0
## 81  2017 September        import     19339 1130    0     184  13   0    6   0
## 82  2017   October        import     20066  988    0     365  37   0   11   0
## 83  2017  November        import     17631  728    0     305  12   0    7   0
## 84  2017  December        import     18404  913    0     243  30   0   72   0
## 85  2018   January        import     17280  863    0     332  37   0   72   0
## 86  2018  February        import     19963  867  164     124   7   0  115   0
## 87  2018     March        import     19477 1099    0     199  15   0    6   0
## 88  2018     April        import     19583 1083    0     161  30   0    2   0
## 89  2018       May        import     18639 1230   37     155  38   0    4   0
## 90  2018      June        import     17924 1174   44     160  37   0    2   0
## 91  2018      July        import     21102  999   36     242  41   0   19   0
## 92  2018    August        import     17014 1028   37     232  21   0    8   0
## 93  2018 September        import     19543 1222   37     179  22   0    7   0
## 94  2018   October        import     19682 1066   66      52   6   0   71   0
## 95  2018  November        import     17114 1213  101     178   0   0  171   0
## 96  2018  December        import     19176 1392  148      68   5   0   79   0
## 97  2019   January        import     19712 1262  119     119  65   0  135   0
## 98  2019  February        import     18869 1037  125     122   0   0  201   0
## 99  2019     March        import     16866  958  183      70   0   0  443   0
## 100 2019     April        import     19411  857  245     203   0   0  115   0
## 101 2019       May        import     19787 1220  174     203   0   0   46   0
## 102 2019      June        import     16821 1573  409     259   0   0  140   0
## 103 2019      July        import     19303 1413  193     118   0   0   70   0
## 104 2019    August        import     19171 1302  138     100   0   0   11   0
## 105 2019 September        import     18714 1227  226     135   0   0  507   0
## 106 2019   October        import     20138 1411  198     177   0   0  699   0
## 107 2019  November        import     18647 1330   61      65   0   0  278   0
## 108 2019  December        import     19515 1218   74      90   0   0  148   0
## 109 2020   January        import     16553 1358    0      26   0   0   34   0
## 110 2020  February        import     14607 1487    0      44   0   0   37   0
## 111 2020     March        import     13677 1218   35     176   0   0   70   0
## 112 2020     April        import     12335  986   38     157   0   2  136   0
## 113 2020       May        import     16859 1228   35     124   0   0    4   0
## 114 2020      June        import     15180 1638   75      86   0   0    2   0
## 115 2020      July        import     15381 1426  131     154   0   0   14   0
## 116 2020    August        import     18290 1394  155     169   0   0    3   0
## 117 2020 September        import     20489 1503  544      82   0   0  246   0
## 118 2020   October        import     19594 1363  124      48   0   0   73   0
## 119 2020  November        import     15235 1521   82     104   0   0   18   0
## 120 2020  December        import     18261 1355  133      29   0   0    9   0
## 121 2021   January        import     18256 1043   74      39   0   0    3   0
## 122 2021  February        import     17259 1046    0      35   0   0    4   0
## 123 2021     March        import     15905 1389    0      37   0   0    1   0
## 124 2021     April        import     15021 1403    0       0   0   0    1   0
## 125 2021       May        import     17387 1695    0       0   0   0    4   0
## 126 2021      June        import     17608 1563  153       0   0   0    6   0
## 127 2021      July        import     17084 1599  412       0   0   0    2   0
## 128 2021    August        import     18340 1581   31      17   0   0    6   0
## 129 2021 September        import     19648 1650    0       0   0   0    4   0
## 130 2021   October        import     19254 1388    0       0   0   0    3   0
## 131 2021  November        import     17589 1249    0       0   0   0    5   0
## 132 2021  December        import     19031 1438    0     110   0   0    5   0
## 133 2022   January        import     21626 1605    0      35   0   0    3   0
## 134 2022  February        import     19644 1363   30      30   0   0    9   0
## 135 2022     March        import     19441 1264  127       2   0   0  115   0
## 136 2022     April        import     20624 1417   63     145   0   0  146   0
## 137 2022       May        import     17637 1574    0      90   0   0    8   0
## 138 2022      June        import     16772 1448  190      76   0   0    2   0
## 139 2022      July        import     18123 1374  327     135   0   0   10   0
## 140 2022    August        import     19003 1778  211      28   0   0    7   0
## 141 2022 September        import     19618 1718  120      88   0   0   12   0
## 142 2022   October        import     20229 1709    0      41   0   0    5   0
## 143 2022  November        import     19285 1647    0     128   0   0   10   0
## 144 2022  December        import     20729 1410    0      98   0   0    4   0
## 145 2011   January        export         0   13 1184     870 295   2 1391   9
## 146 2011  February        export         0   16 1476     800 337   4 2164   9
## 147 2011     March        export         0   13 1359     818 436   2 1587   6
## 148 2011     April        export         0   12 1144     977 418   3 1637   9
## 149 2011       May        export         0   10 1076     998 456   2 1721   9
## 150 2011      June        export         0   16 1295     752 461   3 1916   8
## 151 2011      July        export         0   15  886     635 521   2 2079   9
## 152 2011    August        export         0   16 1052    1025 429   2 1731   0
## 153 2011 September        export         0   15 1422     780 411   3 1705   8
## 154 2011   October        export         0   12 1089     775 307   4 1262   0
## 155 2011  November        export         0   18 1010     842 245   4 1122   8
## 156 2011  December        export         0   17 1528     866 245   4 2092   9
## 157 2012   January        export         0   17 1231     647 299   2 1331   9
## 158 2012  February        export         0   17 1318     638 328   3 1614   0
## 159 2012     March        export         0   13 1479     699 246   3 1717   0
## 160 2012     April        export         0   19 1310     680 267   3 1611   0
## 161 2012       May        export         0   13 1379     756 253   2 1562   0
## 162 2012      June        export         0   15 1527     536 392   2 1795   0
## 163 2012      July        export         0   18 1514     816 455   2 2637   0
## 164 2012    August        export         0   18 1295     924 625   1 2005   0
## 165 2012 September        export         0   19 1419     857 490   2 2546   0
## 166 2012   October        export         0   19 1436     734 426   2 1929   0
## 167 2012  November        export         0   16 1075     656 414   2 1517   0
## 168 2012  December        export         0   17 1675     706 467   1 2200   0
## 169 2013   January        export         0   19 1211     623 551   1 1621   0
## 170 2013  February        export         0   17 1403     739 542   1 1813   0
## 171 2013     March        export         0   17 1489     676 336   1 1813   0
## 172 2013     April        export         0   18 1242     763 415   1 2358   0
## 173 2013       May        export         0   21 1377     832 440   1 2410   0
## 174 2013      June        export         0   18 1305     679 559   1 3371   0
## 175 2013      July        export         0   15 1222     794 536   1 2357   8
## 176 2013    August        export         0   17 1138     586 525   1 2028   8
## 177 2013 September        export         0   20 1301     707 504   1 2580   7
## 178 2013   October        export         0   23 1013     625 380   2 1562   8
## 179 2013  November        export         0   21 1009     614 454   2 2056   0
## 180 2013  December        export         0   22 1536     682 503   1 2498   0
## 181 2014   January        export         0   21 1200     540 234   1 1738   0
## 182 2014  February        export         0   21 1459     522 397   1 2006   6
## 183 2014     March        export         0   17 1404     685 333   1 2156   0
## 184 2014     April        export         0   20 1241     581 401   1 1354   0
## 185 2014       May        export         0   16 1435     572 307   1 1870   0
## 186 2014      June        export         0   21 1276     709 614   1 2814   0
## 187 2014      July        export         0   18 1391     540 516   1 2797   0
## 188 2014    August        export         0   20 1311     756 559   1 2627   0
## 189 2014 September        export         0   19 1667     572 603   1 2277   0
## 190 2014   October        export         0   26 1352     649 502   2 1975   0
## 191 2014  November        export         0   26 1246     404 492   2 2130   0
## 192 2014  December        export         0   28 1067     480 563   2 1815   0
## 193 2015   January        export         0   24  935     576 153   1 1366   0
## 194 2015  February        export         0   19 1341     492 260   1 1495   0
## 195 2015     March        export         0   20 1286     614 377   1 1809   0
## 196 2015     April        export         0   22 1357     683 501   1 2181   0
## 197 2015       May        export         0   19 1537     656 589   1 2432   0
## 198 2015      June        export         0   13 1331     552 669   1 2129   0
## 199 2015      July        export         0    6 1509     358 300   0 1778   0
## 200 2015    August        export         0    5 1438     546 460   0 2264   0
## 201 2015 September        export         0    7 1493     698 386   1 1784   0
## 202 2015   October        export         0   12 1500     581 693   1 2375   0
## 203 2015  November        export         0   17 1573     710 579   1 2353   0
## 204 2015  December        export         0   30 1517     649 718   1 2069   0
## 205 2016   January        export         0   27 1368     494 674   2 2061   0
## 206 2016  February        export         0   29 1561     593 598   1 1437   0
## 207 2016     March        export         0   30 1491     602 643   1 2248   0
## 208 2016     April        export         0   25 1365     667 496   1 2368   0
## 209 2016       May        export         0   22 1160     925 668   1 2848   0
## 210 2016      June        export         0   21 1242     926 535   1 2809   0
## 211 2016      July        export         0   25 1258     745 622   1 2708   0
## 212 2016    August        export         0   24 1102     690 562   1 2417  20
## 213 2016 September        export         0   30 1014     834 702   1 2200   0
## 214 2016   October        export         0   28 1035     802 537   1 1824  40
## 215 2016  November        export         0   26 1204     530 492   1 1751  46
## 216 2016  December        export         0   30 1617     918 742   1 2631  45
## 217 2017   January        export         0   29 1095     749 562   1 2244   0
## 218 2017  February        export         0   29 1333     696 482   1 1956   5
## 219 2017     March        export         0   27 1208     767 570   2 2036   0
## 220 2017     April        export         0   26 1260     917 540   2 2145   4
## 221 2017       May        export         0   26 1060     628 573   1 2793   0
## 222 2017      June        export         0   31 1152     642 578   1 3040   0
## 223 2017      July        export         0   30  996     851 647   1 2946   4
## 224 2017    August        export         0   34 1137     749 558   2 2607   4
## 225 2017 September        export         0   32 1167     658 685   1 2895   0
## 226 2017   October        export         0   35 1195     761 640   1 2704   0
## 227 2017  November        export         0   26 1063     824 621   1 2312   0
## 228 2017  December        export         0   35 1371     710 725   1 2039   0
## 229 2018   January        export         0   29  915     530 492   1 1555   0
## 230 2018  February        export         0   34 1148     542 547   2 1988   0
## 231 2018     March        export         0   34 1206     635 730   2 2447   0
## 232 2018     April        export         0   34 1047     621 653   2 2482   0
## 233 2018       May        export         0   32  840     683 611   2 2844   0
## 234 2018      June        export         0   33 1168     762 651   1 2813   0
## 235 2018      July        export         0   34 1176     563 598   2 2741  33
## 236 2018    August        export         0   29 1110     661 611   1 2311  66
## 237 2018 September        export         0   41 1047     625 647   1 2274   0
## 238 2018   October        export         0   40 1044     456 606   2 1837   0
## 239 2018  November        export         0   36  980     428 496   2 1895   0
## 240 2018  December        export         0   41 1203     459 745   2 2648   0
## 241 2019   January        export         0   38 1002     615 554   2 2017   0
## 242 2019  February        export         0   36 1377     974 473   2 2101   0
## 243 2019     March        export         0   34  841     548 634   2 2220   0
## 244 2019     April        export         0   38 1156     401 484   2 2614   0
## 245 2019       May        export         0   32  904     681 544   2 2357   0
## 246 2019      June        export         0   40 1133     780 720   2 3322   0
## 247 2019      July        export         0   37  994     880 618   1 3119   0
## 248 2019    August        export         0   42  993     736 714   2 3270   0
## 249 2019 September        export         0   42 1329     973 656  21 3143   0
## 250 2019   October        export         0   39  813     787 497  59 2141   0
## 251 2019  November        export         0   41 1027     701 525  21 2390   0
## 252 2019  December        export         0   45 1141     820 488  61 2958   0
## 253 2020   January        export         0   35  932     683 439   0 3404   0
## 254 2020  February        export         0   32 1108     642 304   0 2786   0
## 255 2020     March        export         0   32  985     440 255   1 2094   0
## 256 2020     April        export         0   31 1012     299 225   2 2058   0
## 257 2020       May        export         0   34  874     547 141   1 2790   0
## 258 2020      June        export         0   39  984     609 267   1 2673   0
## 259 2020      July        export         0   36  797     284 176   2 2373   0
## 260 2020    August        export         0   39  895     442 273   2 2244   0
## 261 2020 September        export         0   41  954     611 314   2 2653   0
## 262 2020   October        export         0   46  890     599 304   2 2324   0
## 263 2020  November        export         0   41  884     553 433   1 2109   0
## 264 2020  December        export         0   47 1290     801 413   2 3069   0
## 265 2021   January        export         0   42  934     458 270   1 1880   0
## 266 2021  February        export         0   46 1334     499 418   1 2945   0
## 267 2021     March        export         0   36 1146     608 493   2 2834   0
## 268 2021     April        export         0   31 1002     477 336   1 2259   0
## 269 2021       May        export         0   43  903     635 324   1 2603   0
## 270 2021      June        export         0   45  851     656 292   1 2795   0
## 271 2021      July        export         0   44 1005     551 453   1 2897   0
## 272 2021    August        export         0   46 1035     595 552   1 2781   0
## 273 2021 September        export         0   50 1374     642 569   1 3057   0
## 274 2021   October        export         0   49 1082     511 448   1 2578   0
## 275 2021  November        export         0   45 1217     438 414   1 2415   0
## 276 2021  December        export         0   37 1600     791 617   1 3365   0
## 277 2022   January        export         0   47 1402     611 350   2 2698   0
## 278 2022  February        export         0   47 1157     556 448   1 3063   0
## 279 2022     March        export         0   50 1162     815 591   1 2456   0
## 280 2022     April        export         0   41 1109     355 583   1 2188   0
## 281 2022       May        export         0   39 1018     414 745   0 2365   0
## 282 2022      June        export         0   40  671     468 689   1 2689   0
## 283 2022      July        export         0   43  500     372 639   1 2062   0
## 284 2022    August        export         0   41  842     423 591   1 1979   0
## 285 2022 September        export         0   44 1242     441 624   1 2413   0
## 286 2022   October        export         0   47 1165     333 568   1 1991   0
## 287 2022  November        export         0   42 1379     416 650   1 2150   0
## 288 2022  December        export         0   51 1470     511 786   1 2482   0
##     lobs_lube_oil fuel_oil bitumen petcoke others total
## 1             116       95       7       0    256 17440
## 2             101       21       9       0    281 14979
## 3             105       60       2       0    293 15557
## 4              82      141       5       0    214 15159
## 5             150      183       1       0    241 15586
## 6             133      159       2       0    233 14260
## 7              94       56       1       0    141 13535
## 8             165      137       5       0    344 16224
## 9             131       81       6       0    175 15063
## 10            128       10       3       0    264 18252
## 11            107      171      15       0    240 14936
## 12            123       90      22       0    295 16590
## 13            142      127       7       0    358 16369
## 14            183       63      14       0    334 17131
## 15            144       50       3       0    301 16014
## 16            121       85       4       0    336 16042
## 17            259       52       1       0    570 16798
## 18            171       95       3       0    356 16643
## 19            144       63       8       0    370 17682
## 20            262       88      13       0    375 16958
## 21            101       78       8       0    375 17236
## 22            157      123       5       0    451 19632
## 23            147      113      16       0    322 14472
## 24            146      101      20       0    355 16175
## 25            147      108      25       0    312 17592
## 26            212       60      32       0    467 18651
## 27            140       48       7       0    262 15352
## 28            185      182       7       0    470 17769
## 29            151      147       2       0    441 18970
## 30            103      121       5       0    589 16630
## 31            188      168      11       0    471 16947
## 32            121       40      21       0    414 15699
## 33            230      122      22       0    272 17231
## 34            269       66      20       0    519 17158
## 35            186       96      63       0    436 18010
## 36            158      175      32       0    476 15930
## 37            273      159      36       0    422 18505
## 38            365      124      39       0    491 16663
## 39            111      126      31       0    662 17837
## 40            150       20      16       0    628 16018
## 41            237      106      26       0    646 17793
## 42            136       76      21       0    866 17955
## 43            171       12      30       0    503 17692
## 44            144       61      56       0    659 16628
## 45            129       30      64       0    784 18714
## 46            100       87      52       0    635 19408
## 47            151       53      63       0    772 14813
## 48            180       50      84       0    654 18709
## 49            205       36      91       0    672 17551
## 50            162       49      95       0    959 20052
## 51            195      273      84       0    674 18086
## 52            182       48      50       0    916 20138
## 53            173       50      37       0    974 19824
## 54            191      116      36       0   1092 18122
## 55            150       78      98       0   1043 18059
## 56            209       64      73       0    872 18770
## 57            186       45      93       0    749 19923
## 58            201      270      62       0   1306 21062
## 59            199       30      49       0   1314 19455
## 60            210      111     111       0   1164 21258
## 61            189       80     120       0   1162 21246
## 62            178       96     145       0   1270 20699
## 63            222       89      79       0   1756 20884
## 64            229       79      24       0   1542 20196
## 65            154       27      26       0   2250 22378
## 66            134      135      25       0   1517 20736
## 67            180       79      87       0   1412 21143
## 68            184       70      70       0   1095 21518
## 69            177       84      89       0    956 20819
## 70            175       43      86       0   1193 20127
## 71            169       58      97       0   1021 19046
## 72            140       85     103       0   1412 21429
## 73            210       85      77       0   1358 20881
## 74            179      166     127       0   1362 21059
## 75            192       45      43       0   1334 20486
## 76            174       99      25       0   1527 20717
## 77            141       43      50       0   1689 21345
## 78            195       58      59       0   1055 20094
## 79            222      116      65       0   1420 22316
## 80            221       93      71       0   1050 22028
## 81            216       67     106       0   1577 22638
## 82            238      106      88       0   1057 22956
## 83            298      143     122       0    836 20082
## 84            254      193     115       0   1068 21292
## 85            111      301     104       0   1080 20180
## 86            201      127      92       0    898 22558
## 87            226      195      59       0   1069 22345
## 88            185      164      46       0    897 22151
## 89            217       78      37       0    881 21316
## 90            162       55      54       0    606 20218
## 91            248       50      56       0    414 23207
## 92            214       36      56       0    628 19274
## 93            197      197      59       0   1196 22659
## 94            196       20      85       0   1444 22688
## 95            195      128      88       0   1234 20422
## 96            303       69     143       0   1448 22831
## 97            182       34     113       0   1570 23311
## 98            271       97     137       0   1748 22607
## 99            236      285     126       0   1135 20302
## 100           251      127      93       0   1128 22430
## 101           219      286      52       0    950 22937
## 102           187      371      63       0   1034 20857
## 103           260      325     114       0   1027 22823
## 104           218      257     120       0    827 22144
## 105           180      625     155       0   1154 22923
## 106           269      825     210       0   1030 24957
## 107           207      483     245       0    840 22156
## 108           194      868     200       0    980 23287
## 109           154      379      92     557    216 19369
## 110            91      460     121    1891    165 18903
## 111           118      550     182     706    322 17054
## 112           203     1193     160     875    292 16377
## 113           244      485      86     864    178 20107
## 114           238      238     108     617    101 18283
## 115           271      167     114     747    175 18580
## 116           306      224     161     597   1745 23044
## 117           300      478     228     506    112 24488
## 118           284      381     279     256    241 22643
## 119           252      792     265      86    243 18598
## 120           231     1108     259     553    324 22262
## 121           289      774     302      28    202 21010
## 122           252      585     258     283    124 19846
## 123           208      554     198     255    152 18699
## 124           208      945     155     227    287 18247
## 125           247      697     112      78    209 20429
## 126           247      425     153     211    420 20786
## 127           330      731     196     315    134 20803
## 128           232      564     191     300     95 21357
## 129           334      883     291     975    176 23961
## 130           164      818     238     707    200 22772
## 131           231      948     219     456     90 20787
## 132           317     1056     266     378    100 22701
## 133           230      996     258     892    157 25802
## 134           214      482     251     709    198 22930
## 135           181      601     210     544     95 22580
## 136           222      749     120     793     84 24363
## 137           165      702      64     466    140 20846
## 138           133      567     116     539     89 19932
## 139           212      655     226     855     96 22013
## 140           159      569     346     847     94 23042
## 141           139      963     283     595    130 23666
## 142           139      893     269     516    211 24012
## 143           184      640     296     725     89 23004
## 144           175      745     347    1183    389 25080
## 145             0      403       2       0    428  4597
## 146             0      678       0       0    275  5759
## 147             0      663       2       0    177  5063
## 148             0      766       0       0    262  5228
## 149             0      816       0       0    169  5257
## 150             0      670       0       0    215  5336
## 151             0      587       0       0    290  5024
## 152             0      632       0       0    274  5161
## 153             5      700       0       0    148  5197
## 154             4      761       0       0    144  4358
## 155            12      606       0       0    305  4172
## 156             4      614       0       0    300  5679
## 157             9      491       3       0    173  4212
## 158            14      338       6       0    300  4576
## 159             1      392       0       0    307  4857
## 160             9      508       5       0    558  4970
## 161             7      512       9       0    293  4786
## 162             8      704       6       0    447  5432
## 163             0      635      16       0    313  6406
## 164             5      477      10       0    405  5765
## 165             1      442      10       0    551  6337
## 166             1      521       9       0    371  5448
## 167             1      393       4       0    488  4566
## 168             2      510       9       0    469  6056
## 169             4      495       5       0    400  4930
## 170             0      419       6       0    525  5465
## 171             7      551       5       0    365  5260
## 172             1      560      16       0    342  5716
## 173             1      752      14       0    599  6447
## 174             1      570       9       0    601  7114
## 175             1      577      12       0    603  6126
## 176             1      498      10       0    565  5377
## 177             1      434       9       0    626  6190
## 178             0      288       4       0    200  4105
## 179             1      515       4       0    340  5016
## 180             5      499       0       0    369  6115
## 181             0      355      10       0    365  4464
## 182             1      489       2       0    301  5205
## 183             1      329      12       0    357  5295
## 184             1      460       9       0    359  4427
## 185             1      536       9       0    518  5265
## 186             1      476       0       0    432  6344
## 187             1      376       5       0    482  6127
## 188             1      408       9       0    321  6013
## 189             1      456       8       0    358  5962
## 190             4      344       7       0    310  5171
## 191             1      161       8       0    282  4752
## 192             1      372      14       0    568  4910
## 193             4      363       8       0    313  3743
## 194             1      498      10       0    424  4541
## 195             3      130       8       0    281  4529
## 196             1      162       4       0    319  5231
## 197             1      285      14       0    388  5922
## 198             0      288       9       0    247  5239
## 199             1      133      15       0    330  4430
## 200             0      191       3       0    351  5258
## 201             3      226       7       0    274  4879
## 202             1      164       6       0    292  5625
## 203             1      239       8       0    290  5771
## 204             1      126      10       0    244  5365
## 205             1       88       9       0    158  4882
## 206             3      118       0       0    256  4596
## 207             4      182       6       0    166  5373
## 208             1      197       4       0    242  5366
## 209             1      309       6       0    172  6112
## 210             1      227       4       0    276  6042
## 211             1      332       6       0    458  6156
## 212             1      327       0       0    191  5335
## 213             1      130       0       0    413  5325
## 214             0       94       2       0    829  5192
## 215             1       51       0       0    453  4555
## 216             1      193       2       0    403  6583
## 217             0      112       0       0    381  5173
## 218             0      130       2       0    303  4937
## 219             1       79       2       0    288  4980
## 220             3      381       5       0    255  5538
## 221             4      321      25       0    441  5872
## 222             1      418       6       0    393  6262
## 223             1      272      12       0    228  5988
## 224             1      228       2       0    293  5615
## 225             1       85       2       0    378  5904
## 226             1      192       2       0    473  6004
## 227             1      145       0       0    253  5246
## 228             1      162       4       0    262  5310
## 229             0       15       0       0    276  3813
## 230             0       35       0       0    248  4544
## 231             1       74       3       0    207  5339
## 232             1      194       0       0    310  5344
## 233             1      339       2       0    242  5596
## 234             1      325       5       0    314  6073
## 235             0      310       2       0    280  5739
## 236             1       75       0       0    378  5243
## 237             1      394       4       0    169  5203
## 238             1      270       0       0    290  4546
## 239             1       74       5       0    227  4144
## 240             1       92       0       0    324  5515
## 241             0       55       4       0    121  4408
## 242             1       99       3       0    369  5435
## 243             1      127       1       0    282  4690
## 244             1      152       1       0    222  5071
## 245             1      171       4       0    608  5304
## 246             1      365       2       0    219  6584
## 247             1      157       2       0    163  5972
## 248             1      152       2       0    221  6133
## 249             1       33       0       0    286  6484
## 250             1        0       4       0    308  4649
## 251             1      103       2       0    224  5035
## 252             0      114       0       0    297  5924
## 253             0      178       0      59    309  6039
## 254             3      235       0     207    436  5753
## 255             5      137       0     242    224  4415
## 256             3       62       0      54    175  3921
## 257             0        0       0       7    197  4591
## 258             1       21       2       6    198  4801
## 259             1       82       2       0     87  3840
## 260             0       28       0       0    139  4062
## 261             0       48       2       0     67  4692
## 262             0      112       0       1    151  4429
## 263             1       75       0       1     50  4148
## 264             1      200       0       0    256  6079
## 265             0       80       0       1    251  3917
## 266             0      232       0       0    260  5735
## 267             0      200       0       0    193  5512
## 268             0      299       0       0    294  4699
## 269             0      155       0      42     98  4804
## 270             0      127       2      42    131  4942
## 271             0      111       4      52    190  5308
## 272             0       68       0       0    115  5193
## 273             1      138       0       0    143  5975
## 274             0      165       0       0    237  5071
## 275             5       90       0      44    186  4855
## 276             1       92       0       6    232  6742
## 277             5       42       0       4    275  5436
## 278             0       77       0      33    300  5682
## 279             1      127       1      36    267  5507
## 280             1      186       0      11    214  4689
## 281             0      221       0      38    398  5238
## 282             1      156       2      16    254  4987
## 283             0      229       2       0    123  3971
## 284             1      159       0       0    229  4266
## 285             1      248       0       0    684  5698
## 286             1      179       0       0    215  4500
## 287             0       76       0      22    320  5056
## 288             1      141       3     123    435  6004
sun_import <- subset(sun, import_export == "import")

sun_import <- sun_import %>%
  select(-total)

t <- pivot_longer(sun_import, cols = c(crude_oil:others), names_to = "Product", values_to = "Quantity")

t
## # A tibble: 1,872 × 5
##     year months  import_export Product       Quantity
##    <int> <chr>   <chr>         <chr>            <int>
##  1  2011 January import        crude_oil        15737
##  2  2011 January import        lpg                419
##  3  2011 January import        ms                  20
##  4  2011 January import        naphtha            153
##  5  2011 January import        atf                  0
##  6  2011 January import        sko                129
##  7  2011 January import        hsd                508
##  8  2011 January import        ldo                  0
##  9  2011 January import        lobs_lube_oil      116
## 10  2011 January import        fuel_oil            95
## # ℹ 1,862 more rows
dout <- data_to_hierarchical(t, c(year, Product, months), Quantity)

hchart(dout, type="sunburst")